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Classification of Web Applications Using AiFlow Features

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Web, Artificial Intelligence and Network Applications (WAINA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1150))

Abstract

With the increasing of complexity and volume of network traffic, more advanced methods of traffic analysis are required to continue producing useful results. Conventional methods of solving this problem include lexicographical pattern analysis, where a signature is created manually and then compared with incoming traffic in the hopes of detecting a matching signature. The main issue of such methods is its inability to adapt to even minor changes in the signature of the target application architecture. In this paper we introduce a new flow format AiFlow, designed specifically to assist in the association of traffic with application based on a wider set of criteria. This flow format coupled with a sufficient artificial intelligence (AI), could be capable of identifying both the dynamic and static elements that define the behavior of a network-enabled application. Further, the system would be equipped to adapt to the inevitable variations in application behavior over time.

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Acknowledgments

This project was supported in part by funding from a Keene State College Faculty Development Grant and an undergraduate research grant from The School of Sciences, Sustainability and Health, Keene State College.

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Authors and Affiliations

  1. Department of Computer Science, Keene State College, USNH, Keene, USA

    Nathanael Mercaldo & Wei Lu

Authors
  1. Nathanael Mercaldo
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  2. Wei Lu
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Corresponding author

Correspondence to Wei Lu .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Electrical Engineering and Information Technology, University of Naples “Frederico II”, Naples, Italy

    Flora Amato

  3. Department of Political Science, University of Campania Luigi Vanvitelli, Caserta, Italy

    Francesco Moscato

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

  5. Department of Advanced Sciences, Hosei University, Tokyo, Japan

    Makoto Takizawa

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Mercaldo, N., Lu, W. (2020). Classification of Web Applications Using AiFlow Features. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2020. Advances in Intelligent Systems and Computing, vol 1150. Springer, Cham. https://doi.org/10.1007/978-3-030-44038-1_35

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